Competing in the World of AI
Executive Technology Board | Veldhoven, April 29, 2026
AI is moving faster than most enterprises can comfortably absorb, and that acceleration is increasingly shaped by the realities of compute, infrastructure, and concentration. This session brings the Executive Technology Board into the center of that discussion, hosted in a part of the technology stack that offers a useful vantage point on where AI is headed and what that may mean for enterprise strategy.
Digital transformation is no longer best understood as a technology program. It is increasingly about how large enterprises compete, allocate capital, and adapt their operating models to deliver outcomes. The question is no longer whether to invest in AI. It is whether the investment thesis is sound, whether the architecture is resilient, and whether the sequencing can hold up under real execution pressure. Technology sovereignty, concentration risk, and regulatory posture are no longer peripheral concerns. They are becoming practical constraints on what can be built, how quickly, and on whose infrastructure.
Outcomes for the Day
Peer intelligence
A candid exchange on what is working, what is stalling, what sequencing is holding up, and which assumptions are being revised in practice.
Inside view
A grounded look at how these questions appear in one of the world’s most demanding engineering environments.
The goal is not consensus. It is collective intelligence.
Pre-Work Reflection
Please come prepared to engage with specificity and candor.
- An AI investment that has generated measurable business value, and how that value is being assessed
- An AI investment that has stalled or underperformed, and the most important reason why
- One strategic or architectural decision currently being worked through
- One assumption embedded in the current AI strategy that may prove wrong
Session 1 | Transformation Roadmaps & Capital Allocation
The core question: Is the current AI investment thesis sound, and is the sequencing holding up in practice?
Discussion prompts
- Where is AI investment concentrating over the next 12 to 18 months? What is being deprioritized?
- What sequencing logic is proving most effective: foundational platforms first, or use-case value first?
- What has changed in the investment thesis over the past year, and what forced that change?
Key tension
How should enterprises balance the need to build durable foundations with the need to show value early enough to sustain momentum, funding, and organizational belief?
Session 2 | Tech Sovereignty & Concentration Risk
The core question: What does a resilient AI strategy look like when the infrastructure beneath it is concentrated, contested, and increasingly shaped by regulation?
Discussion prompts
- Where does concentration risk feel most material today: compute, models, platforms, or data infrastructure?
- How is regulation shaping architecture decisions in practice?
- What choices are being made to preserve optionality, and what is the real cost of doing so?
Key tension
When does standardization create necessary focus and speed, and when does it create dependencies that will be difficult to unwind later?
Session 3 | Beyond Process: AI in Products and Physical Systems
The core question: What is required to move from AI as a workflow tool to AI embedded in products, systems, and physical operations?
Discussion prompts
- Where is AI beginning to reshape the product itself, not just the process behind it?
- What new technical, organizational, or governance capabilities does that shift require?
- For industries beyond manufacturing, is AI at the physical layer an important frontier or still a secondary concern?
Key tension
How far should enterprises push beyond process optimization today, and what separates justified ambition from premature overreach?
ASML Inside View & Innovation Tour
The day will also include an inside look at how ASML is thinking about innovation, transformation, and AI in one of the world’s most demanding engineering environments. The purpose is not a customer presentation, but a peer-level view into how these questions look when the product is physical, the systems are highly complex, and the cost of failure is exceptionally high.
Three questions to carry into the tour:
- How does digital transformation look different when the product is physical rather than purely digital?
- What does AI governance require when reliability, safety, and precision are central?
- What does a position near the front end of the compute supply chain reveal about concentration risk that many enterprises do not see directly?
Executive Technology Board (c)